code: def _validate_tensordock_creds(self, api_key: str, api_token: str):
      client = api_client.TensorDockAPIClient(
          api_key=api_key, api_token=api_token
      )
      if not client.auth_test():
          raise_invalid_credentials_error(
              fields=[["creds", "api_key"], ["creds", "api_token"]]
          )
  
file_path: dstack/src/dstack/_internal/server/services/backends/configurators/tensordock.py
imports: import json
  from typing import List
  from dstack._internal.core.backends.tensordock import TensorDockBackend, api_client
  from dstack._internal.core.backends.tensordock.config import TensorDockConfig
  from dstack._internal.core.models.backends.base import BackendType, ConfigElementValue, ConfigMultiElement
  from dstack._internal.core.models.backends.tensordock import AnyTensorDockConfigInfo, TensorDockConfigInfo, TensorDockConfigInfoWithCreds, TensorDockConfigInfoWithCredsPartial, TensorDockConfigValues, TensorDockCreds, TensorDockStoredConfig
  from dstack._internal.server.models import BackendModel, ProjectModel
  from dstack._internal.server.services.backends.configurators.base import Configurator, raise_invalid_credentials_error
label_desc: Use image node_id 7 for calling the TensorDockConfigurator obj's underlying member method code with example usage: obj._validate_tensordock_creds(api_key, api_token) without return types